检索结果-内蒙古大学图书馆

2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Ramneshkar, B. Krishnan, R. Bala Kumar, N.Rajesh Karthikeyan, B. Manikandan, G. School of Computing Sastra Deemed University Thanjavur India Srinivasa Ramanujan Centre Sastra Deemed University Department of Computer Science and Engineering Kumbakonam India

ISBN: (纸本)9798350313987

Digital mode of communication is widely used for exchanging various kinds of data through internet. The data that is being transmitted may be used in sensitive applications. Thus, those data have to be secured from various kinds of attacks and must ensure basic security services as well. One such kind of data is Image data which is used in medical imaging and some other sensitive fields as well. There are many algorithms to protect and secure the images during transmission but the algorithm and their security has to be modified constantly to cope up with the technological advancements. So, in this enhanced work, an authentication-based image scrambling algorithm using hybrid chaotic maps and SHA is proposed. RSA provides the initial-values for the chaotic-map. Improved LS will be used to generate random values for XOR operation. SBOX will be generated by using both Improved LS and Henon map. Authentication message will be embedded into the image and it will be XORed and scrambled thrice (SBOX, Arnold and Sub-Image based). Receiver will decrypt and verify the message. This algorithm is expected to be faster, provide good security and resist several attacks. © 2023 IEEE.

关键词： Arnold Transform Authentication Henan Map Image Encryption RSA SHA

来源：评论

学校读者我要写书评

暂无评论

Advancing Optical Tomography Image Analysis: Exploring Convolutional Neural Network Model Variants for Retinal Damage Detection 10

Advancing Optical Tomography Image Analysis: Exploring Convo...

引用

10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Sathyan, S. Chanchal, M. Raghul, S. Jeyakumar, G. Amrita Vishwa Vidyapeetham Amrita School of Physical Sciences Department of Mathematics Coimbatore India Cmr Institute of Technology Department of Information Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350382471

Retina is a vital component of the eye;it plays a crucial role in visual perception. Any damage to the retina can lead to vision impairment and severe ocular diseases. Early detection and accurate diagnosis of retinal conditions is crucial. In the domain of medical image analysis, especially within the scope of retinal imaging, convolutional neural network (CNN)-based deep learning models have exhibited promising results. This paper involves the detection of retinal conditions such as Diabetic Macular Edema (DME), Choroidal Neovascularization (CNV) and Drusen. The paper presents a comparative study of CNN models for the detection of these retinal damages using Optical Coherence Tomography (OCT) images. This study focuses on evaluating the performance of popular CNN architectures, like Residual Networks (ResNet), Dense Convolutional Networks (DenseNet), Inception Networks, Visual Geometry Group (VGG). Also, the paper provides a comparative analysis of different depth variants of deep learning models such as ResNet (18, 50 and 101), DenseNet (121, 169, and 201), Inception-V3, Inception-ResNet-V2, and VGG (16 and 19). These models are assessed on a dataset containing OCT images of Normal, DME, CNV and Drusen retinal conditions. The effectiveness of the models are evaluated using evaluation metrics such as accuracy, precision, recall and F1 score. Additionally, visualizations such as confusion matrix, training accuracy versus validation accuracy plots, training loss versus validation loss plots are utilized to provide a better understanding of the model performance. The idea is to explore the impact of depth on the model performance and understand how deeper models demonstrate an enhanced ability to learn complex features and capture intricate details within the retinal data. Exploring these depth variants aims to provide insights into the advantages and potential trade-offs associated with increasing depth of deep learning models for retinal damage detection tasks. © 2

关键词： choroidal neovascularization deep learning DenseNet diabetic macular edema drusen Inception networks medical image analysis ocular diseases optical coherence tomography (OCT) ResNet retina retinal imaging VGG

来源：评论

学校读者我要写书评

暂无评论

Grocery Purchase through Blockchain System 7

Grocery Purchase through Blockchain System

引用

7th IEEE Pune Section International Conference, PuneCon 2024

作者： Kumar, Boddu Manoj Rajeswari, G. Thanush, B.V. Krishna, Vamsi Sree, E. Divija Balakrishnan, Arunkumar Sathyabama Institute of Science and Technology School of Computer Science Engineering with Blockchain Technology Tamil Nadu Chennai600119 India Sathyabama Institute of Science and Technology School of Computer Science Engineering Tamil Nadu Chennai600119 India VIT-AP University School of Computer Science Engineering India Crm Institute of Technology School of Computer Science Engineering Karnataka Bengaluru India Sree Vidyanikethan Engineering College Rangampeta School of Computer Science Engineering with Artificial Intelligence Tirupati517102 India Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Department of Information Technology Manipal India

ISBN: (纸本)9798331527822

The integration of blockchain technology into the grocery purchasing process offers a transformative approach to enhancing transparency, security, and efficiency. This paper presents a comprehensive framework for a blockchain-based grocery system, detailing each step from user registration and identity verification to product listing, smart contract creation, and real-time inventory management. Consumers can place orders with confidence, knowing that payments are securely processed and supply chain logistics are fully transparent. The use of IoT devices ensures quality control during transportation, while smart contracts automate delivery and receipt confirmation. Additionally, the system supports consumer feedback and dispute resolution through immutable records and predefined arbitration mechanisms. This innovative application of blockchain technology aims to revolutionize the grocery sector, fostering trust and accountability among all stakeholders involved. Future research will explore the potential for AI integration and address scalability and interoperability challenges. © 2024 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

A Survey Analysis on Decentralized Land Registry System Using Blockchain and Smart Contracts 1

A Survey Analysis on Decentralized Land Registry System Usin...

引用

1st International Conference on computer science and Emerging Technologies, CSET 2023

作者： Narayanaprakash, K. Malarchelvi, P. D. Sheba Kezia Ranjithkumar, S. Sridevi, R. Anitha, P. Kumar, N.Suresh Alliance University Anekal Department of Computer Science and Engineering Bengaluru562 106 India Saranathan College of Engineering Department of Computer Science and Engineering Tiruchirappalli India School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Computer Science and Engineering Trichy India Oasys Institute of Technology Department of Computer Science and Engineering Pulivalam Trichy India Bangalore India

ISBN: (纸本)9798350341737

This study investigates the potential use of blockchain technology and smart contracts to construct a decentralised land registry system. It looks at the problems with traditional land registry systems and provides a technical breakdown of how to create a blockchain-based land registry system. The research also evaluates the countries that have already adopted such systems and discusses the possible adoption of a blockchain-based land register system in India. The implementation of a blockchain-based land registration system, per the research, can increase the security and efficacy of land transactions, reduce fraud and mistakes, and promote economic growth. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

EmoSync: Facial Emotion Detection for Adaptive Music Playback 3

EmoSync: Facial Emotion Detection for Adaptive Music Playbac...

引用

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

作者： Devarajan, Devikanniga Rajkumar, K. GITAM Deemed to be University Computer Science and Engineering Nagadenahalli Doddabalpur Karnataka Bangalore561203 India SRM Institute of Science and Technology Department of Data Science and Business Systems School of Computing Tamil Nadu Kattankulathur603 203 India

ISBN: (纸本)9798350372120

This work investigates using Convolutional Neural Networks (CNN) and VGGNet architecture, for realtime emotion detection. Raw data from the FER-2013 dataset is transformed from CSV format into organized image directories, segmented by distinct emotions. The resulting model, equipped with convolutional, pooling, and dense layers, effectively classifies emotions from 48x48 grayscale images. In application, the model overlays detected emotions onto a webcam stream. An integrated music player module synchronizes music with the subject's emotions. Overall, this research explores a comprehensive interactive system focused on recognizing and responding to human emotions. Without further training data, our model, to the best of our understanding, achieves modern single-network accuracy of 74.57% on FER2013 © 2024 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

Evaluation Method of Object Control Capability for Children Based on Nonlinear Dynamics 23

Evaluation Method of Object Control Capability for Children ...

引用

3rd International Conference on Bioinformatics and Intelligent computing, BIC 2023

作者： Wang, Huaijun Li, Chao Zhang, Dongsheng Li, Junhuai Key Laboratory of Network Computing and Security Technology School of Computer Science and Engineering Xi an University of Technology Xi'an China

ISBN: (纸本)9798400700200

DCD (Developmental Coordination Disorder) has become a global problem, and several studies have shown that early detection and intervention are important for the prevention and treatment of DCD in children. To address the problems of low intelligence, simple assessment indexes and single dimension in assessing children's motor coordination, a method based on non-linear dynamics is proposed to assess children's object control ability. Using the child's in-situ ball tapping as the test item, the Kinect and inertial sensors are used to collect hand spatial position information and human motion biomechanical signals during the ball tapping process. The complexity of the signal is reflected by the sample entropy of the motion signal. The approach suggested in this thesis, which uses non-linear kinetic characteristics, enhances the accuracy of behavioral and developmental identification by 1% to 3% when compared to existing methods. The experiments prove that the proposed method has a better recognition rate and stability than the traditional assessment methods. © 2023 ACM.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Assessment of a Novel Single-Channel EEG Method for Automated Recognition of Sleep Phases 15

Assessment of a Novel Single-Channel EEG Method for Automate...

引用

15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Mahapatra, Rajesh Kumar Upadhyay, Harsh Kondaveeti, Hari Kishan Satapathy, Santosh Kumar Rajput, Nitin Singh Tripathy, Santosh Kumar Pandit Deendayal Energy University Information and Communication Technology Gujarat Gandhinagar India VIT-AP University School of Computer Science Engineering Andhra Pradesh India Vit Bhopal University School of Computing Science and Engineering Sehore India

ISBN: (纸本)9798350370249

Assessing sleep stages is crucial for identifying and managing sleep disorders such as REM sleep disorders and narcolepsy. Automating this process not only expedites detection but also enhances diagnostic accuracy. Thus, this research used the discrete wavelet transform technique and a convolutional neural network to automate sleep stage identification. In this proposed method, the single-channel EEG undergoes decomposition into four levels via discrete wavelet transform, followed by extraction of statistical features from these levels. Subsequently, employing CNN, relevant features are selected and utilized as input to the model. The CNN model achieved high accuracies of 95.81% five-class (five sleep stages). This proposed approach for automated sleep stage detection has the potential to expedite the identification of sleep stages and even sleep disorders, and it can accommodate large-scale EEG datasets. However, it's important to note that this approach was solely evaluated on one dataset, underscoring the need for validation across other databases in future investigations. © 2024 IEEE.

关键词： component formatting insert (key words) style styling

来源：评论

学校读者我要写书评

暂无评论

Prediction of Rental Demands using different Machine Learning Algorithms

Prediction of Rental Demands using different Machine Learnin...

引用

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Ravikumar, S. Vijay, K. Pavithra, S. Prithi, S. Kannan, Sriram Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineeirng Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India VIT University School of Computer Science and Engineering Chennai India SRM IST School of Computing Department of Computational Intelligence Kattankulathur India Sri Sivasubramaniya Nadar College of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350348217

A Bike rental expectation conjectures the interest for bikes rentals in reliance of climate conditions like the temperature and calendric data. In bike rental frameworks, it is vital that the managers have to realize the number of bikes to be placed in each and every station. This include empowers them in or-ganizing the necessary number of bikes at each station and choose whether a specific station needs to have additional number of bikes or it is not re-quired. In this venture we will foresee the no of bikes required for explicit climate and climatic conditions. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine Learning Algorithms in Thyroid Disease Prediction 23th

Comparative Analysis of Machine Learning Algorithms in Thyro...

引用

23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Preethiya, T. Tyagi, Amit Kumar Pandiarajan, T. Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Kanchipuram 603203 India Department of Fashion Technology National Institute of Fashion Technology New Delhi India Department of Computer Science Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031648120

Thyroid disease is estimated to be the most common illness in the twenty-first century. The thyroid hormones are produced by a butterfly-shaped gland in the throat. The crucial function these hormones play in bodily metabolism, mental health, and general well-being. In this study, we present a method for accurately analysing thyroid function in an unbalanced dataset using Machine Learning (ML) algorithms. This dataset's accuracy score is ambiguous because most target variable classes are 1. Performance measurements are accuracy and recall, but when class distribution is asymmetrical, the F1-score balances the other parameters. The performance is evaluated using the F1-score, which is one of the best output metrics for unbalanced classification tasks. Simulation results shows that the Decision Tree (DT) algorithm outperforms the other algorithms with an F1-score of 0.9957, the Area Under Curve (AUC) score of 0.9917 and the kappa coefficient of 0.978 in the disease prediction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A two-stage method with twin autoencoders for the degradation trajectories prediction of lithium-ion batteries

引用

Journal of Energy Chemistry 2025年第4期103卷 759-772页

作者： Lei Cai Jing Yan Haiyan Jin Jinhao Meng Jichang Peng Bin Wang Wei Liang Remus Teodorescu School of Computer Science and Engineering Xi’an University of TechnologyXi’an 710048ShaanxiChina School of Electrical Engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Smart Grid Research Institute Nanjing Institute of TechnologyNanjing 211167JiangsuChina Department of Energy Aalborg UniversityAalborg 9220Denmark

To predict the lithium-ion(Li-ion)battery degradation trajectory in the early phase,arranging the maintenance of battery energy storage systems is of great ***,under different operation conditions,Li-ion batteries present distinct degradation patterns,and it is challenging to capture negligible capacity fade in early *** the data-driven method showing promising performance,insufficient data is still a big issue since the ageing experiments on the batteries are too slow and *** this study,we proposed twin autoencoders integrated into a two-stage method to predict the early cycles'degradation *** two-stage method can properly predict the degradation from course to *** twin autoencoders serve as a feature extractor and a synthetic data generator,***,a learning procedure based on the long-short term memory(LSTM)network is designed to hybridize the learning process between the real and synthetic *** performance of the proposed method is verified on three datasets,and the experimental results show that the proposed method can achieve accurate predictions compared to its competitors.

关键词： Battery degradation trajectory Early prediction Autoencoder Synthetic data generation

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：