检索结果-内蒙古大学图书馆

2nd International Conference on Advances in Computation, Communication and Information technology, ICAICCIT 2024

作者： Jadhav, Swati Darekar, Smeet Deshmukh, Anurag Deore, Bhavesh Datir, Dev Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9798331541217

Digital privacy and secure communication are under increasing threats, making strong methods of protection of sensitive data ever more important. Steganography is the art of concealing information within seemingly innocuous media, but the traditional techniques usually cannot resist advanced steganalysis methods. One such hybrid steganographic method has been proposed, embedding encryption onto color analysis for serving the dual purpose of ensuring more security and making the data hidden less perceivable. This technique tries to enhance both imperceptibility and resistance towards detection by embedding encrypted messages into strategically selected parts of the image where modifying is less likely to be detected by both the naked eye observer and the automated detection mechanisms. This is achieved by carrying out a color analysis that selects the optimal embedding regions with regard to texturing complexity and luminance contrast. In this work, a proposal for secure transmission is also developed using steganalysis keys that allow only the authorized parties to decrypt and reach the hidden information. Consequently, the strong point of this approach considers this to be a highly secure and imperceptible means for covert data communication, suitable for applications in the military, government, and digital watermarking. © 2024 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Real-Time Network Monitoring and Reporting Using Network Intrusion Detection System 9

Real-Time Network Monitoring and Reporting Using Network Int...

引用

9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Lonare, M.B. Joshi, Bhuvan Chandra Tripathy, Satyam Kumar Kumar, Shivam Tiwari, Shivanshu Army Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350394474

The increased participation in digital networks for communication, commerce, and critical infrastructure, calls for a robust Network Intrusion Detection System. This paper systematically examines the current landscape of NIDS, by analyzing the methodologies, algorithms, and technologies used in finding different forms of network threats. The paper begins by presenting the fundamental principle of the Intrusion Detection System and the evolving threat scenario and the benefits of using ML and Deep Learning when employed in this use case. We also dive into the categorization of NIDS into Signature-Based, anomaly-based, and Hybrid approaches. Evaluating each category's strengths and weaknesses. The paper aims to provide a comprehensive discussion and comparison of the various techniques proposed like MCF-MVO-ANN, an Intrusion detection system based on scalable K-means and Random Forest, etc. By synthesizing current knowledge this paper aims to serve as a valuable resource for researchers, practitioners, and decision-makers in the field of cybersecurity. © 2024 IEEE.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

Sign Language Translation Across Multiple Languages 4

Sign Language Translation Across Multiple Languages

引用

4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Antad, Sonali M. Chakrabarty, Siddhartha Bhat, Sneha Bisen, Somrath Jain, Sneha Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350349856

Sign Language serves as the only mode of communication for people who are speech and hearing disabled. Despite this, they face many difficulties in communication due to different sign languages across the world using different signs and symbols. This project aims to bridge this gap and make communication easy and accessible for all. Through the utilization of Convolutional Neural Networks (CNN) and other deep learning algorithms, the project provides a platform to people to choose between Indian Sign Language and American Sign Language and further provides translation to multiple Indian regional languages to improve communication between people. This serves a two-way purpose by enabling people who are trained in different sign languages to communicate efficiently as well as providing written text in multiple languages for people who cannot interpret sign language and are proficient only in regional languages. This comprehensive strategy strives to eliminate communication barriers, contributing to a more equitable society. This innovative project has the potential to significantly enhance communication inclusivity and accessibility for the global deaf and hard of hearing community. © 2024 IEEE.

关键词： Audition

来源：评论

学校读者我要写书评

暂无评论

Stock Indexes Community Identification Using BAT-Modified Optimization Algorithm

引用

SN computer Science 2024年第8期5卷 1-14页

作者： Aggarwal, Kirti Arora, Anuja Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Noida India

Stock price accelerates interest and preference of the young generation to explore the stock market with elicit interest. An autopilot system is needed where users choose beneficial stocks of their choice without paying attention to the manual inspection or implication. This study aims to form highly correlated stock communities based on fluctuations in stock price which will be helpful in the prediction and decision-making of users about their expenditure in the stock market. For the enormous volume of stock price time series data, the opted data representation method is the network which is generated with the help of a data statistical correlation test. Another research challenge was to detect the community in an optimized manner due to complex stock networks. For the same, BAT optimization algorithm and a proposed BAT-modified (BAT-M) algorithm are applied for complex stock network community formation. The better community formation results showcase that BAT-M gives better performance in comparison to the standard BAT algorithm on various performance evaluation factors. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： BAT Community detection Correlation Modularity Nature-inspired Optimization Stock indexes Stock network

来源：评论

学校读者我要写书评

暂无评论

Satellite Image to Map Translation using GANs 15

Satellite Image to Map Translation using GANs

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Phatangare, Sheetal Khalifa, Mohammed Mansoor Kharche, Sejal Khatib, Amaan Kshirsagar, Atharva Vishwakarma Institute of Technology Computer Engineering Department Pune India

ISBN: (纸本)9798331300579

Generative adversarial networks (GANs) are a promising method for learning deep representations without spending a lot of time on data for annotated training. They accomplish this by obtaining signals that are back propagated through a competitive mechanism in-transforming two networks. The possible representations of a variety of applications may employ the knowledge gathered by GANs, image synthesis, semantic image editing, fashion categorization, transmission, and image super-resolution. The goal of this research article is to give an overview of GANs. the signal processing community, utilizing well-known whenever feasible, use concepts and analogies. Additionally, to recognize various training techniques and building GANs, we also highlight lingering issues with their theory and utilization. © Grenze Scientific Society, 2024.

关键词： Gallium nitride

来源：评论

学校读者我要写书评

暂无评论

Enhancing Public Safety through Real-time Weapon Detection: A Deep Learning Approach 3

Enhancing Public Safety through Real-time Weapon Detection: ...

引用

3rd International Conference for Advancement in technology, ICONAT 2024

作者： Dass, J. Maria Arockia Suresh, A. Swathi, K. Shalini, Paidimuddala Sinha, N A Yaswanth Kotholla Uday Kiran, U. Siddharth Institute of Engineering & Technology Department of Computer Science and Engineering Andhra Pradesh Chittoor India

ISBN: (纸本)9798350354171

Date In response to the imperative need for mitigating criminal activities and ensuring public safety, this research proposes a novel approach leveraging deep learning techniques for real-time weapon detection. In contemporary society, criminal acts pose significant threats to both individuals and the broader community, necessitating proactive measures to counter such offenses swiftly. By harnessing advanced technologies, particularly deep learning algorithms like YOLOv7-tiny, this study intend to create a robust system capable of identifying weapons in surveillance footage captured by CCTV cameras. The project begins with the meticulous collection of datasets from reputable research sources, ensuring diverse and comprehensive samples for training the deep learning model. Subsequently, these datasets undergo rigorous pre-processing steps to optimize them for training, including resizing images to the required format. To facilitate accurate annotation and labelling of the dataset, advanced tools like Robo flow software are employed, streamlining the process and enhancing efficiency. Upon completion of the pre-processing phase, the YOLOv7-tiny algorithm is deployed for training the model on the annotated datasets. Through iterative training and validation processes, the model is fine-tuned to achieve optimal performance in weapon detection tasks. Once trained, the model is capable of swiftly and accurately identifying weapons in real-time surveillance footage. This project presents an effective solution for real-time weapon detection in public spaces, leveraging deep learning algorithms and advanced software tools. © 2024 IEEE.

关键词： Image annotation

来源：评论

学校读者我要写书评

暂无评论

Using Unsupervised Learning to detect Fraud in Cryptocurrency 3

Using Unsupervised Learning to detect Fraud in Cryptocurrenc...

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Chordia, Sankalp Nilesh Shinde, Sandeep Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350354348

Bitcoin, the most popular form of cryptocurrency, operates independently of central banks or governmental entities. The emphasis on anonymity complicates the task of tracing cryptocurrency payments linked to illicit activities or criminal transactions. Consequently, ransomware developers exploit this environment to extort ransom by encrypting valuable user information. Numerous research endeavors have explored the application of machine learning techniques to detect fraudulent activities within cryptocurrency transactions. However, there is a notable absence of studies showcasing the practical implementation of such methods using real-time blockchain data. The present study is structured into two main sections. Firstly, we delineate the development of various features utilized for training purposes. Subsequently, our approach will be validated using real-time Bitcoin data. The other section highlights the use of open source investigation tool (OSINT) to carry forward the cryptocurrency investigation by taking the input from previous findings. OSINT involves the retrieval of information from a range of publicly accessible data sources, while offering a viable approach to address the difficulties associated with extracting and aggregating intelligence from diverse publicly available information channels and social platforms. Thus narrowing down the search investigation by exploiting the pseudonymity of Bitcoin and tracing back the wallet and IP addresses' digital and physical identity. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Forecasting Renewable Energy Generation: A Predictive Modelling Approach 2

Forecasting Renewable Energy Generation: A Predictive Modell...

引用

2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Mondal, Priotosh Bhatia, Aditi Panjwani, Roshini Dokare, Indu Ves Institute of Technology Department of Computer Engineering Mumbai India

ISBN: (纸本)9798350368413

India's rapid urbanization demands innovative solutions to address energy consumption patterns while reducing reliance on fossil fuels. This research paper explores the application of predictive modelling techniques like Multilayer Perceptron and Polynomial Regression to forecast solar energy generation and Long Short-Term Memory (LSTM) models to forecast wind energy generation, thereby facilitating efficient energy planning in major Indian cities. The proposed system aims to create a web-based platform that integrates these predictive models to display real-time temperature conditions and the corresponding amount of energy that solar and wind sources can provide in specific locations, thus promoting smart cities and smart homes. By utilizing the website, energy planners will be able to compare the generated energy from wind and solar sources, enabling informed decisions on which resource best meets the energy requirements of housing settlements. © 2024 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network

引用

Digital Communications and Networks 2024年第2期10卷 292-303页

作者： Yuteng Xiao Kaijian Xia Hongsheng Yin Yu-Dong Zhang Zhenjiang Qian Zhaoyang Liu Yuehan Liang Xiaodan Li School of Information and Control Engineering China University of Mining and TechnologyXuzhou221116China Department of Informatics University of LeicesterLeicesterLE17RHUK The Affiliated Changshu Hospital of Soochow University Changshu215500China School of Computer Science and Engineering Changshu Institute of TechnologySuzhou215500China

The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other ***,it is important to construct a digital twin ***,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted *** this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)***,we fuse the spatial-temporal graph based on the interrelationship of spatial ***,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding ***,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)*** module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like *** dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted *** on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.

关键词： Adaptive adjacency matrix Digital twin Graph convolutional network Multivariate time series prediction Spatial-temporal graph

来源：评论

学校读者我要写书评

暂无评论

Noval Approach using Image Detection to Identify Diseases in Fruit Plants (Apple) 9

Noval Approach using Image Detection to Identify Diseases in...

引用

9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Kadam, Anup Dwivedi, Anand Prakash Shekhar, Amatya Sree, Dasari Hema Prajapat, Avnish Army Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350394474

In the face of the critical imperative to feed a projected global population of 9 billion people by 2050, India, harboring one of the world's largest populations, grapples with formidable challenges in food production, exacerbated by substantial crop losses. An alarming statistic reveals that approximately 30 percent of India's agricultural yield succumbs to various factors, including pests, diseases, and post-harvest inefficiencies. This staggering loss not only poses a severe threat to India's food security but also contributes significantly to the broader global food crisis. Traditional solutions, often reliant on chemical pesticides, not only fall short in effectively addressing these challenges but also incur adverse environmental impacts, further exacerbating the sustainability dilemma. In response to this pressing issue, a groundbreaking research project emerges, advocating for innovative approaches that seamlessly integrate advanced technology, data-driven insights, and inclusivity to forge a resilient and sustainable agricultural ecosystem. This transformative initiative specifically targets the identification of plant diseases in apple trees, recognizing the potential ripple effects on broader agricultural practices. By leveraging cutting-edge technology like CNN and CAE the research introduces a comprehensive methodology that not only efficiently identifies and manages plant diseases but also holds the promise of sustainable crop management and economic stability. © 2024 IEEE.

关键词： Crops

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：