检索结果-内蒙古大学图书馆

International Conference on computer and Communications Technologies (ICCCT)

作者： Vasanthan P S. Srinivasan Dept. of Information Technology Sri Sairam Engineering College Dept. of Computer Science and Engineering R.M.D Engineering College

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

The concerns about the security created by the PC have gotten more advanced and complicated. Interruption detection is a pragmatic subject in the area of PC security whose essential target is to identify uncommon assault or attacks and to guarantee the safety of inside frameworks. This paper likewise suggests a semi-class interruption recognition strategy that joins various classifiers to mastermind exemptions and regular activities in a PC framework. In the consideration preference tree learning-iterative dichotomy 3, the maltreatment recognition method is developed and is gathered by using the cumulative knowledge based on the peculiarity detection system performed by one class- uphold vector machine. As of late, individuals have paid more thoughtfulness regarding Id/interruption avoidance framework, which is firmly identified with the insurance and use of framework the executives. A couple of AI principles including neural framework, genetic programming, and progressed uphold vector machines, Bayesian framework, multivariate adaptable backslide splines, feathery deduction systems and other analogical frameworks has been scrutinized for the layout of interruption identification framework. In this article, we suggest a combination strategy dependent on dTl-Id3 and OC-SVM assess the presentation of the extended procedure by utilizing a particular dataset and a hybrid technique to upgrade the precision of IdS/IPS when stood out from a solitary help vector machine.

关键词： Surveys Support vector machines Urban areas Vectors data models Regulation Safety Registers Splines (mathematics) Pragmatics

来源：评论

学校读者我要写书评

暂无评论

Advanced Fake Review detection via Aspect Extraction and TPA-BilSTM-CSSA 2

Advanced Fake Review Detection via Aspect Extraction and TPA...

引用

2nd IEEE International Conference on data Science and Network Security, ICdSNS 2024

作者： Thakkar, Nilam Kumar, Arvind Sukumar, P. Sarode, deepika G. Patil, Harshal Vijayakumar, E. Ldrp - Institute of Technology & Research Ksv University Svkm Department of Information & Technology Gujarat India School of Computer Applications Mriirs Haryana Faridabad India Nandha Engineering College Department of Computer Science and Engineering Erode India Dr.D.Y.Patil Institute of Technology Department of Engineering Pune Pimpri India Iilm University Department of Computer Science and Engineering Greater Noida India KIT-Kalaignar Karunanidhi Institute of Technology Department of Mca Coimbatore India

ISBN: (纸本)9798350373110

In recent years, methods to detect bogus reviews have attracted the attention of numerous businesses and educational organizations. In order for reviews to accurately represent genuine user experiences and opinions, it is quite challenging to identify fake reviews. Supervised learning has been a popular approach to tackle the problem. The issue is that manually marking fake reviews with a degree of reliability that would be useful for training is very difficult, if not impossible. There are three phases to the suggested strategy preprocessing, feature extraction, and training the model. This proposed employs a series of preprocessing techniques to get the dataset's raw data ready for computational operations. dimensionality reduction and the quantification of content-related and text-segment-related features comprise feature extraction. To train the model, a TPA-BilSTM-CSSA was used. On average, the suggested method achieves a higher accuracy of 93.71% than BilSTM and CSSA. © 2024 IEEE.

关键词： Fake detection

来源：评论

学校读者我要写书评

暂无评论

An Advanced decentralized Architecture enabled logical Identity based Encryption logic using Blockchain Assistance 4

An Advanced Decentralized Architecture enabled Logical Ident...

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Geetha, R. Kalpana, S. Roopa Chandrika, R. Preetha, M. Santhoshini, P. Nithila, Ezhil E Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Eee Saveetha School of Engineering Tamil Nadu Chennai India Department of Computer Science Dubai United Arab Emirates Karpagam Academy of Higher Education Department of Computer Science and Engineering Tamil Nadu Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Rmd Engineering College Department of Electronics and Communications Engineering Tamil Nadu Chennai India Veltech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Ece Tamil Nadu Chennai India

ISBN: (纸本)9798350349900

Using electronic signatures, blockchain technology, and identity-based encryption, essential documents may be certified and electronic contracts can be signed. All of the system's nodes, operations, and transactions may benefit from blockchain technology's distributed ledgers. This study introduces a novel encryption system, decentralized Identity based Encryption logic (dIEl), and assesses its efficacy by comparing it to the established Identity based Encryption (IBE) scheme. In order to guarantee the privacy and confidentiality of patients' data in cloud health systems, the suggested technique offers first-rate security using bilinear pairings. Additionally, this strategy authenticates users through challenge-response procedures. Furthermore, the suggested method guarantees the accuracy and integrity of shared data via the use of blockchain technology. Using the standard model, we can confirm that the suggested protocol is valid and that it is secure. Because all nodes are contributing data, cyberspace is more open and behavior can be more easily tracked. data certification and the contract signing procedure are both finished and in compliance. Users may protect themselves from fraud and identity theft with the help of the Identity based Management system's encryption features. When used together, these two technologies will provide a safer method of data storage while yet preserving user privacy. © 2024 IEEE.

关键词： decentralized finance

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

Recognition of Identifying Malicious Cyber Attack Intention in Cyber Physical System

Recognition of Identifying Malicious Cyber Attack Intention ...

引用

International Conference on computer and Communications Technologies (ICCCT)

作者： P Vasanthan S. Srinivasan Dept. of Information Technology Sri Sairam Engineering College Dept. of Computer Science and Engineering R.M.D Engineering College

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

As the threat over the cyber-attack is predominantly increasing in every aspects such as based on network traffic, spoofing, phishing attacks the intrusion detection system is used. The network layer is maliciously attacked by the intruder. The intruder tries to capture network packets of the connection between client and server. Based upon the encryption standard, the intruder tries to comprise the user system. Intrusion cannot be easily detected since it is a manual process. In this novel approach, deep learning reinforcement technique is implemented. The bidirectional end to end communication along with the Bayesian inverse reinforcement learning is used to detect the malicious cyber intention in cyber physical system. Inverse Bayesian reinforcement learning technique is initiated to identify the behavior of the pattern recognition and to resample the dataset. This deals with the risk factor and determines whether the connection is comprised. In this work, the novel application is introduced with deep reinforcement learning to identify the intruder. The intrusion detection is labeled in dataset. These dataset implements reward functions to detect the intrusion over the cps.

关键词： Uncertainty Phishing Intrusion detection Telecommunication traffic Probability distribution Bayes methods Pattern recognition Servers Cyberattack Standards

来源：评论

学校读者我要写书评

暂无评论

Experimental study of hardness and corrosion properties of AZ91 magnesium alloy after electroless nano composite coating

引用

Materials Today: Proceedings 2022年 62卷 2926-2929页

作者： Sayyad, dr Farook Sayyad, dr Shabnam Ansari, dr. Md. Imran Mechanical Engineering Department. Dr. D. Y. Patil School of Engineering Pune India Associate Professor Computer Engineering Department. AISSMS College of Engineering Pune India Robotics & Automation Department. Bharati Vidyappeth Pune India

Magnesium and its numerous alloys have excellent rigidity, low density, and electromagnetic protection properties, making them ideal for usage in numerous industrial components. Magnesium alloys have a significant disadvantage in terms of corrosion and hardness, which restricts their practical uses. One of the most recent ways for improving the corrosion and hardness of Mg alloys is electro-less nano-coating. The experimental research of corrosion and hardness of AZ91 Mg Alloy due to nano composite coating procedures of ENi-B-TiO2is examined in this study. It would be useful to conduct a thorough examination, including experimental analysis, into the possibilities of increasing the deposit efficiency and characteristics of composite deposits by designing a suitable bath composition and operating circumstances. It has been discovered that as the concentration of titania particles increases, so does the surface hardness of coatings. The optimal concentration of second-phase (titania) particles and bath agitation are also examined in order to get superior surface properties following nano coating. Following this nano coating, the materials may be employed for a variety of materials engineering applications. © 2022

关键词： Surface properties

来源：评论

学校读者我要写书评

暂无评论

TRACING THE MOTION IN HIGH-SPEEd VIdEO FRAMES USING dEEP lEARNING

TRACING THE MOTION IN HIGH-SPEED VIDEO FRAMES USING DEEP LEA...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Gayathri, R. Harsha, B.K. Sharmiladevi, d. Sajitha, l.P. Rao, Vuda Sreenivasa Nirmala, G. Department of ECE Rajalakshmi Engineering College Tamilnadu Chennai India Department of ECE CMR Institute of Technology Karnataka Bengaluru India Department of Electronics and Communication Engineering Sona College of Technology Tamilnadu Salem India Department of Computer Science and Business System R. M. K Engineering College Tamilnadu Kavaraipettai India Department of CSE Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Computer Science and Engineering R.M.D Engineering College Chennai India

ISBN: (纸本)9798350305708

One of the most important jobs of a self-driving vehicle's visual system is to identify and categorize obstacles along the route. Cars need to be detected, categorized, localized, and linked across frames if they are to be tracked. With the low cost and high utility of visual information, vision-based technologies have gained popularity for this purpose. In this paper, we develop a deep learning-based motion tracking from high-speed video frames. The model is developed using deep convolutional neural network that makes it to be applicable for classification of objects in the video frames. The deep convolutional neural network classifies the obstacles present in the pathway and offers a better classification pattern than the conventional models. © 2023 IEEE.

关键词： Application Convolutional Neural Network deep learning High-Speed Video Motion Vehicle Video Frames

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Examination of the Advancements in deep learning Models for Enhanced disease Prediction

A Comprehensive Examination of the Advancements in Deep Lear...

引用

Smart Technologies for Sustainable development Goals (ICSTSdG), International Conference on

作者： Sasirekha. K Joe Prathap P.M Department of Computer Science & Business Systems R.M.D Engineering College Chennai India Department of Computer Science & Engineering R.M.D Engineering College Chennai India

ISBN: (数字)9798331516284

ISBN: (纸本)9798331516291

The field of human disease prediction holds great promise for revolutionizing healthcare through early diagnosis and customized treatment plans. Therefore, studies on thisregion are crucial. A short time ago, deep learning has been increasingly incorporated into many different sectors of artificial intelligence, owing to its exceptional performance and ability to autonomously acquire features. In the field of medicine, particularly in the realm of deep neural learning, the accuracy rate surpasses that of doctors. This paper provides an outline of the challenges faced by deep learning systems in predicting human diseases. despite these challenges, deep learning has great promise for enhancing human disease detection and prediction. Addressing these issues will require collaboration between machine learning researchers, healthcare professionals, and policymakers in order to guarantee that deep learning models in healthcare are safe, effective, and morally sound.

关键词： deep learning Knowledge engineering Precision medicine Predictive models Regulation Proposals Internet of Things Sustainable development Medical diagnostic imaging diseases

来源：评论

学校读者我要写书评

暂无评论

Congestion Control Enhancement in TCP

Congestion Control Enhancement in TCP

引用

International Conference on Network Security and Blockchain Technology, ICNSBT 2023

作者： Chikkareddi, Vishwanath Chikaraddi, Vinaykumar Chinchali, Santosh Kusur, Chidanand B.L.D.E.A’s V.P. Dr. P.G. Halakatti College of Engineering and Technology Vijayapura India Vijayapura India

ISBN: (纸本)9789819944323

Congestion control in TCP is a crucial task. There are many congestion control techniques exists. The aim of these methods is to prevent congestion and also to maximize the use of bandwidth available. The implementation of a single congestion control algorithm under varied environments of networks still remains a daunting task, as the performance improvement parameters differ for different TCP. This paper presents a novel approach to deal with congestion which requires communication between layers for improving estimation of congestion. The better the congestion estimation better will be the counter measures can be done. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte ltd.

关键词： Transmission control protocol

来源：评论

学校读者我要写书评

暂无评论

Enhancing lung disease diagnosis through Meta learning: A Framework Utilizing Few-Shot learning Techniques

Enhancing Lung Disease Diagnosis through Meta Learning: A Fr...

引用

Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： S Anandhi Sterlin Rani devakadacham J Manikandan M. Shanthalakshmi Computer Science and Engineering Rajalakshmi Engineering College Chennai India Computer Science and Engineering R. M. D. Engineering College Kavaraipettai India Department of Information Technology St. Joseph’s College of Engineering Chennai India Computer Science and Engineering Sri Venkateswara College of Engineering Chennai India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

Ailments of the lungs stand out as the most common medical conditions that are encountered in the healthcare industry. Manual assessment, which frequently involves the use of chest X-ray images and visual inspection, is something that is commonly used in traditional diagnostic approaches. This method can be time-consuming and prone to errors. deep learning techniques, despite their potency, require a significant quantity of data in order to achieve optimal performance. These techniques frequently produce unsatisfactory results when applied to tiny datasets. In order to solve these issues, the research being conducted here intends to make use of a meta-learning technique, more precisely few-shot learning. ClAHE, which stands for contrast limited adaptive histogram equalization, is used to do the initial preprocessing of the raw dataset in the framework that has been proposed. A segmentation procedure is performed on the pre-processed images by utilizing the UNET model, which guarantees accurate separation of lung nodules. After the nodules have been segmented, they are subjected to feature extraction by transfer learning. This is accomplished by employing the CheXNet model that has been pre-trained on the Chest Xray14 dataset, which contains 14 chest abnormalities. After the features have been extracted, they are transferred into a classifier, which is then used to distinguish between a variety of abnormalities and normal circumstances. The new component of this research resides in the implementation of few-shot learning techniques within the classifier, allowing efficient image categorization even with insufficient data. A promising strategy to intensifying the precision and efficiency of lung disease diagnosis in the healthcare sector is presented by the technique that has been developed.

关键词： Metalearning Image segmentation Visualization Pulmonary diseases Computational modeling lung Inspection

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：