检索结果-内蒙古大学图书馆

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Mukherjee, Subhayan Chatterjee, Anusuya Chandrakar, Khushbu Saxena, Sandeep Asansol Engineering College Artificial Intelligence and Machine Learning Asansol India Asansol Engineering College Electronics and Communication Engineering Asansol India Asansol Engineering College Computer Science and Engineering Asansol India Greater Noida Institute of Technology Computer Science and Engineering Delhi India

ISBN: (纸本)9798350356816

Speech has been the catalyst for natural human communication, and any disability in this field presents a significant barrier to normal communication. Sign language is the primary method of communication, but its education is not available in all parts of the country. This research paper titled 'artificial intelligence Powered Chatbots for the Speech Disabled and Hearing Impaired using Feedforward Neural Network' provides a novel integration of artificial intelligence to guide and empower the daily routines of people with speech disabilities. By introducing a specialized chatbot tailored to the unique needs of speech-disabled individuals, this paper addresses the pressing need for advanced assistive technologies in the daily lives of speech-disabled individuals. This paper underscores the transformative impact of AI in fostering inclusivity and empowerment in the lives of people with disabilities. © 2024 IEEE.

关键词： Assistive technology

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Food Identification and Waste Reduction Solution with Built-in Nutritional Tracking using machine learning 8

A Comprehensive Food Identification and Waste Reduction Solu...

引用

8th International Conference on Inventive Systems and Control, ICISC 202

作者： Jonathan, J. Benjamin, Ruth Moly Prasad, Gunji Prem Karunya Institute of Technology and Sciences Computer Science Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Artificial Intelligence and Machine Learning Coimbatore India Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350386578

Food Solutions and Nutrition Checker is an innovative and comprehensive project aimed at providing users with a reliable tool to identify various foods and dishes, while also offering a custom-built database for detecting fresh and wasted food items. With this system, users can easily determine the nutritional value of different foods, making informed decisions about their dietary choices. This study incorporates advanced technology that enables the recognition of a wide range of food items. By simply capturing an image or specifying the dish, users can obtain accurate information about the food, including its ingredients and origin. This feature is particularly helpful for individuals with specific dietary needs or restrictions, allowing them to easily identify suitable menu options. Additionally, this study includes a custom-built data system that helps to identify fresh and wasted food. By analyzing factors such as expiration dates, storage conditions, and quality indicators, the proposed system can determine the freshness status of various food items. This capability promotes food waste reduction by enabling users to make informed decisions regarding the consumption or disposal of perishable goods. Moreover, this study incorporates a nutritional tracker that provides users with comprehensive information regarding the nutritional composition of different foods. This feature includes details such as calorie count, macronutrient breakdown, vitamins, and minerals, empowering users to make healthier food choices aligned with their dietary goals and requirements. Overall, the proposed model offers a holistic approach for food identification, waste reduction, and nutritional tracking. By incorporating advanced technology and a robust database, this study aims to facilitate informed decision-making and promote healthier dietary practices. © 2024 IEEE.

关键词： Food ingredients

来源：评论

学校读者我要写书评

暂无评论

Organic Farming Automation to Revolutionize the Agricultural Industry Than Traditional Farming Practices Using IOT and Technological Development

Organic Farming Automation to Revolutionize the Agricultural...

引用

International Conference on Robotics, Control, Automation and artificial intelligence, RCAAI 2023

作者： Geetha Rani, E. Chalasani, Ramadevi Anusha, D. Dhanalakshmi, M. Vadlamudi, Sandyarani Department of Computer Science Engineering Alliance University Karnataka Bengaluru India Department of Computer Science Engineering Sir C R Reddy College of Engineering Andhra Pradesh Eluru India Department of CSE-Artificial Intelligence and Machine Learning SRKIT Andhra Pradesh Vijayawada India Department of Computer Science Engineering NHCE Karnataka Bengaluru India Department of Aritficial Intelligence and Machine Learning New Horizon College of Engineeing Karnataka Bengaluru India

ISBN: (纸本)9789819746491

Agriculture has remained the spine of human sustenance on earth. Since times unknown, humans have learned and developed methods to produce food and other resources for their livelihood. Agriculture has seen large developments, especially in the last century. Scientific methods have accelerated the process of agriculture to a large extent. These developments have improved productivity by leaps and bounds. Though these developments come with a lot of benefits, they also include several demerits that adversely affect the soil, humans, and livestock. To retain and multiply the benefits contributed by this scientific development and to overcome the demerits and challenges faced in today’s agricultural practices, this paper aims at discussing methodologies that can be used to build an agricultural model that is much simpler and more efficient. The model aims at automation using IoT that could lead to minimized labor efforts by almost refraining human intervention in agricultural practices. machine learning algorithms can be used for weather and soil-based crop detection for better productivity. The downside caused due to the use of synthetic chemicals can be overcome using organic methods. A web portal to facilitate direct producer-to-consumer retail can be deployed to curb the exploitation of farmers by the elimination of middlemen. Hence, the paper aims at developing an agricultural model based on IoT, machine learning, organic farming, and a web portal for direct producer-to-consumer retail. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Relational Model and Improvised DSR Assisted Framework for Secure Wireless Communication 1

引用

Computing science, Communication and Security - 4th International Conference, COMS2 2023, Revised Selected Papers

作者： Rajani, K.C. Manjunatha, S. Rakesh, V.S. Bhavana, P. Department of Artificial Intelligence and Machine Learning Cambridge Institute of Technology Bengaluru India Department of Computer Science and Engineering Cambridge Institute of Technology Bengaluru India

ISBN: (数字)9783031405648

ISBN: (纸本)9783031405631

Wireless communications offer a wide range of application with cost- effective communication establishment used in both commercial and domestic purpose. Owing to the presence of decentralized environment in Wireless Communications, it is quite a potential issue for monitoring the regular behavior of any wireless node while performing data propagation. The proposed study states that a wireless node in wireless communication environment plays a role of either normal node or malicious node with completely two different polarities of intention. However, the essential concern is mainly towards the selfish node, which is basically a normal node and owing to certain reason their behavior comes under suspicious zone. Irrespective of various forms of security attacks, identifying malicious node behavior is the most challenging security concern in wireless communication, which has yet not received a proper security solution. The proposed work presents a novel idea of security towards resisting adversarial impact of selfish node and routing mis-behavior present in wireless communications environment. The 1st-framework introduces a retaliation model where a novel role of node called as an auxiliary node is introduced to cater up the routing demands along with security demands. This module performs identification of a malicious routing mis-behavior based on evaluation carried out for the control message being propagated to the auxiliary node. The 2nd-framework further introduces a group friendly architecture where a probability-based modelling is carried out considering various possible set of actions to be executed by normal and selfish node. The model also presents a solution towards security threat prevention by encouraging the selfish node to perform cooperation. The study outcome is benchmarked with existing technique to see that proposed system offers a good balance between security performance and data transmission performance in wireless communication. © 2023, The Author

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

Echo Insights: YouTube Sentiment Analysis App

Echo Insights: YouTube Sentiment Analysis App

引用

2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Vijay, K. Sharan Adhitya, C.D. Senthilnaathan, K. Jaeyalakshmi, M. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331541170

ISBN: (纸本)9798331541187

In an era where social media is getting a wider attraction seeing an improvement in content creators than consumers, ECHO INSIGHTS is a tool for analyzing YouTube video sentiments. This mainly focusses on creating an analytical tool that inputs a YouTube video link from user and uses YouTube API V3 to fetch comments from the video and organize them into a dataframe using pandas. For global audacity, these extracted comments are translated into English using Google trans library in Python. Subsequently, each of the fetched results are assigned with sentiments using Vader, a pre trained sentiment analysis model with a better accuracy of 96%. Then the analyzed results are displayed in a intuitive dashboard designed using streamlit enabling users to interpret sentiment patterns in the content. The dashboard offers various visualization contents like, good and bad comments based on Vader sentiment providing a clear view on sentiments of comments. Additionally, a summarized sentiment score is also displayed, providing general tone of the video. One of the additional features of out webapp is Wordcloud, a python library that plots most comments used or relevant words in the fetched comments representing a quicker glance in video engagement and users' opinions on video. ECHO INSIGHTS aims to empower content creators with better analysis and a healthier component and understanding of audience feedback and engagement with videos. Overall enabling users and creators with continuous improvement and optimization of their content, thus acting as a goof asset by translating raw comments till overall sentiment facilitating deeper connection with audience and crafting contents more efficiently. © 2024 IEEE.

关键词： Sentiment Analysis Streamlit Vader Wordcloud YouTube API

来源：评论

学校读者我要写书评

暂无评论

Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System

引用

Neutrosophic Sets and Systems 2025年 80卷 540-563页

作者： Shams, M.Y. Darwesh, M.R. Bhatnagar, Roheet Al-Sattary, N.S.A. Salama, A.A. Ghoname, M.S. Deptartment of Machine Learning Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheihk33516 Egypt Department of Agriculture Engineering Faculty of Agriculture Tanta University Tanta31527 Egypt Department of Food Processing Faculty of Industry and Energy Samannoud Technological University Egypt Department of Computer Science and Engineering Manipal University Rajasthan Jaipur India Department of Mathematics and Computer Science Faculty of Science Port Said University Egypt

This paper demonstrates the feasibility of using an electronic nose to assess fish quality by analyzing air quality and examining volatile organic compounds (VOCs) alongside physical variables, with pH, protein content, and VOCs serving as chemical reference points. artificial intelligence algorithms were employed to predict quality and calculate regression coefficients. Using the reference neural network algorithm based on chemical and physical compounds, regression coefficients (R values) achieved were 0.99, 0.98, and 0.97, respectively. Additionally, ANFIS (Adaptive Neuro-Fuzzy Inference System) produced R values of 0.99, 0.85, and 0.98. Both fuzzy logic and ANFIS proved effective for predicting fish quality. Image processing techniques, including histogram analysis, color mapping, and edge detection, were also applied to assess fish quality. To enhance the inference process, Neutrosophic Logic-Enhanced Fuzzy Logic Systems were utilized, addressing uncertainty and imprecision in fish quality assessment. Neutrosophic logic combines fuzzy logic's partial truth with indeterminacy, represented by three membership functions: truth, indeterminacy, and falsity. Neutrosophic fuzzy inference integrates steps like neutrosophication, rule evaluation, aggregation, and defuzzification, ensuring improved expressiveness and fidelity. For instance, neutrosophic fuzzy rules evaluated fish freshness and appearance to determine quality ratings such as poor, good, or excellent. This integration enhances decision-making by accurately modeling complex real-world uncertainties. These methods, combining electronic nose technology, artificial intelligence, and neutrosophic inference, provide a robust, non-destructive, and cost-effective approach to detecting spoilage in fillet fish. © 2025, University of New Mexico. All rights reserved.

关键词： Volatile organic compounds

来源：评论

学校读者我要写书评

暂无评论

Life Expectancy Prediction using machine learning Technique - KNN 3

Life Expectancy Prediction using Machine Learning Technique ...

引用

3rd IEEE World Conference on Applied intelligence and Computing, AIC 2024

作者： Narooka, Preeti Vashistha, Aarushi Mitra, Priyanka Derashri, Gulisha School of Computer Science Engineering Manipal University Department of Artificial Intelligence and Machine Learning Rajasthan Jaipur303007 India Jaipur Engineering College and Research Centre Department of Computer Science and Engineering Jaipur303905 India Jaipur Engineering College and Research Centre Department of Computer Science and Engineering Jaipur India

ISBN: (纸本)9798350384598

In the modern world, life expectancy turns out to be the most valuable factor in determining population's health. Today, it is more crucial to predict the future because life is more precarious due to a variety of circumstances, including social, economic, environmental, educational, lifestyle, and health conditions. The machine learning algorithm KNN for life expectancy is presented in this work. The dataset gathered for this study is separated into a training set (70%) and a test set (30%), and the forecasts precision is examined. To avoid misclassification, KNN needs a larger sample size, and the best K are chosen more in accordance with cross-validation experience than with strong statistical theory. © 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

Predicting the Spread of Covid-19 Using machine as a Service (MaaS) Through Modified Apriori Algorithm

Predicting the Spread of Covid-19 Using Machine as a Service...

引用

International Conference on Smart Systems and Wireless Communication, SSWC 2024

作者： Sett, Samir Kumar Sett, Aishik Ghosh, Anupam Department of Computer Application Techno India Kolkata India ITC Infotech Kolkata India Department of Computer Science and Engineering and Department of Artificial Intelligence & Machine Learning Netaji Subhash Engineering College Kolkata India

ISBN: (纸本)9789819613472

The cloud computing and machine learning is one of growing technology in the field of computer science. In recent years, the word "Cloud" is like a cup of tea in our daily lives. Every day, a significant volume of data is produced by different IT sectors, banking sectors, e-commerce websites like flipkart. It provides the organization with consistency, scalability, and strong enumerating power. It also delivers eminence service by generating proper outcomes in a brief amount of time. The objective of this paper is to predict the growth of Covid-19 virus in near future using machine as a Service (MaaS) through modified Apriori algorithm. In this paper, we will obtain the working graph of the algorithm. The result is also analyzed by obtaining the graphs for confidence against lift, support against confidence. At last, a running time comparative graph for modified apriori and apriori is shown for a certain duration of time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Apriori Cloud computing Confidence Covid-19 MaaS Support

来源：评论

学校读者我要写书评

暂无评论

Blockchain for Secure and Efficient Crowdfunding: An Optimized Particle Swarm Approach 9

Blockchain for Secure and Efficient Crowdfunding: An Optimiz...

引用

9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Lakshmanan, M. Mala, G.S. Anandha Poorni, R. Ilamurugan, G. Sriramkumar, R. Gnanavel, R. Dayananda Sagar University Department of Artificial Intelligence and Machine Learning Bangalore India Easwari Engineering College Anna Univeristy Department of Computer Science and Engineering Chennai India Sri Venkateswara College of Engineering Sriperumbudur India

ISBN: (纸本)9798350377972

Crowdfunding, a method of raising capital through collective contributions, often faces challenges related to transaction efficiency, security, and transparency. Blockchain addresses these issues by providing a decentralized, transparent, and secure environment for transactions, while smart contracts automate the fund release process based on predefined conditions. PSO, a nature-inspired optimization algorithm, is applied to optimize various crowdfunding parameters such as funding strategies, donor behavior, and campaign success. By combining PSO with blockchain, the proposed model improves both the speed and security of crowdfunding transactions. This research presents an innovative approach to enhancing crowdfunding platforms by integrating Particle Swarm Optimization (PSO) with blockchain technology. Proposed Model achieves a 30% reduction in transaction time and a 40% improvement in security. This is achieved through the use of a Merkle tree for secure data storage and smart contracts to ensure efficient and automated fund management. The integration of PSO further optimizes key parameters, such as fund distribution and reward allocation, leading to a more efficient and transparent platform. The combination of these technologies results in a crowdfunding experience that is not only faster but also more secure and reliable, enabling global, borderless funding while minimizing fraud and enhancing trust among participants. This research highlights the potential of OPSA-enabled blockchain solutions to transform the crowdfunding landscape, offering a more efficient, secure, and transparent funding platform. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

Systematic Literature Review on Industry Revolution 4.0 to Predict Maintenance and Life Time of machines in Manufacturing Industry 3

Systematic Literature Review on Industry Revolution 4.0 to P...

引用

3rd International Conference on artificial intelligence and Smart Energy, ICAIS 2023

作者： Sowmya, P. Ravichandran, Sathish Kumar Rakshitha Department of Robotics and Artificial Intelligence Karnataka Nitte India Christ University School of Engineering and Technology Department of Computer Science Karnataka Bangalore India Department of Artificial Intelligence and Machine Learning Karnataka Nitte India

ISBN: (纸本)9781665462167

Industry 4.0 is digitized revolution for manufacturers or companies where in new technologies are imbibed into their production system for their day-to-day operations or activities. So that their overall economic needs and efficiency can be improved. In manufacturing industry maintenance of the equipment is the key concern. When the equipment requires maintenance, it has to be done at the earliest, failing which companies will have to face consequences in terms of loss of customers, time and money. Solution is provided to this problem in terms of a technique called predictive maintenance. The content of the article focuses on different predictive maintenance strategies, which help manufacturers to forecast if equipment/component will fail so that its maintenance and repair can be scheduled exactly before the component fails. The results will be useful for manufacturers to understand the importance of industry 4.0 for predictive maintenance. © 2023 IEEE.

关键词： Industry 4.0

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：