检索结果-内蒙古大学图书馆

3rd International Conference on artificial intelligence For Internet of Things, AIIoT 2024

作者： Manaswitha, K. Issac, Titus Silas, Salaja Terance, J Sebastian Division of Data Science and Cyber Security Karunya Institute of Technology and Sciences Coimbatore India Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Artificial Intelligence and Machine Learning Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9798350372120

In recent years, there have been significant advancements in Unmanned Aerial Vehicles (UAVs), leading to their integration into everyday life. UAVs are constrained by limited energy, communication, and localization. The various challenges in UAV research include localization, routing, navigation, and task assignment. Recently, UAV swarms have been employed across a wide range of applications. This study focuses on solving task assignment problems within UAV swarms, considering the unique multi-objective resource constraints of UAVs. The work explores the feasibility of adopting the Red Fox Algorithm to address the task assignment problem in UAV swarms. The investigation examines two primary input parameters: Task Energy Demand and distance. The evaluation includes energy utilization and shortest distance as performance metrics. Notably, the proposed approach outperforms the Particle Swarm Optimization Algorithm (PSO), resulting in a 17.47% lower energy utilization while maintaining a 17.83% reduction in the shortest distance travelled. By leveraging the Red Fox Algorithm, the work aims to enhance the efficiency and effectiveness of task allocation in UAV swarms, contributing to their broader adoption across various applications. © 2024 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Predicting House Price Model : A Comprehensive Analysis with Random Forest and Decision Tree Method 3

Predicting House Price Model : A Comprehensive Analysis with...

引用

3rd International Conference for Innovation in Technology, INOCON 2024

作者： Sharma, Mansi Sharma, Deepak Burle, Rushikesh Patil, Pawan Joge, Isha Puri, Chetan Datta Meghe Institute of Higher Education and Research Department of Computer Science and Design Wardha India Department of Commerce & Management Sciences Maharashtra Wardha India Datta Meghe Institute of Higher Education and Research Department of Artificial Intelligence and Machine Learning Wardha India Datta Meghe Institute of Higher Education and Research Department of Artificial Intelligence and Data Science Wardha India

ISBN: (纸本)9798350381931

This paper explores the field of predicting property prices through a thorough comparison of several regression techniques. Linear regression, decision tree regression, random forest regression, K-neighbors regression, gradient boosting regression, and XGBoost regression are the regression models that are being examined. Finding the best model to reliably estimate house prices based on a set of features is the *** dataset used in this study includes location, bedroom count, square footage, and other relevant parameters that are known to affect property values. Each regression model is trained and tested on this dataset using a methodical evaluation procedure, and its performance is evaluated using important metrics including R-squared, Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and overall correctness. predicting house prices mainly use harlfoxem (Owner) repository of housing dataset will contain the homes sold between May 2014 and May 2015 with 21613 entries and 21 attribute were used to evaluate the performance of machine learning prediction model. For practitioners and scholars working in real estate, housing market analysis, and related sectors, this study offers insightful information. It emphasizes how crucial it is to properly choose regression techniques depending on the particulars of the prediction task and the distinct qualities of the dataset. © 2024 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Development of Punjabi Automatic Speech Recognition Application for Mobile Devices 7

Development of Punjabi Automatic Speech Recognition Applicat...

引用

2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Mittal, Puneet Sharma, Sukhwinder Manipal University Jaipur Department of Artificial Intelligence & Machine Learning Jaipur India Manipal University Jaipur Department of Data Science & Engineering Jaipur India

ISBN: (纸本)9798350304268

Speech recognition based mobile device applications are gaining popularity due to their ease of use, flexibility as well as ability to provide hands-free access to device features and functions for persons without hands or with disabilities like blindness. The increased accuracy of Automatic Speech Recognition (ASR) systems and support to multiple languages is further motivating the researchers to develop such applications. The development of an application for mobile device helps to validate the applicability of an ASR system in real world environment. An android based speech recognition application for calling and messaging features has been designed and developed in this paper. User can send message or call to any phone number or contact stored in the mobile phone using Punjabi speech. Punjabi based ASR system having pronunciation dictionary, acoustic model and language model is used to implement the underlying speech recognition for Punjabi speakers. Speech user interface has been designed using Android, while AndroidPocketSphinx has been used as speech decoder. The successfully running application has been tested for multiple male and female native Punjabi speakers, followed by thorough performance analysis. The results shown are quite optimistic with a very low combined error of 1.6% for all female speakers and 2.1% for all male speakers. The application gives 98.4% success rate or recognition accuracy for female speakers and 97.9% for male speakers for the underlying Punjabi based ASR system. © 2023 IEEE.

关键词： Acoustic model AndroidPocketSphinx ASR Language Model Pronunciation Dictionary Speech Recognition

来源：评论

学校读者我要写书评

暂无评论

Edge Computing: An Overview 14

Edge Computing: An Overview

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Shettar, Girish B. Devangavi, Anil D. Basaveshwar Engineering College Department of Information Science and Engineering Bagalkote India Basaveshwar Engineering College Department of Artificial Intelligence & Machine Learning Bagalkote India

In current era, the Edge computing archetype has captured substantial recognition in various educational universities and IT sector. Edge computing assists as an opportunity and act as a key empowering influence for different technological innovation like Augmented Reality (AR), 5th Generation Mobile Network (5G), communications between vehicles (V2V) by interfacing amenities or services at the cloud, Internet of Things (IoT) and providing resources to end clients. The Edge computing architype anticipates to reduce latency, faster digital experiences, location mindfulness backing to time-delicate applications such as voice over IP, live streaming videos, multimedia teleconferencing. This paper comprehensively presents the concepts of the edge computing and in contrast to the cloud computing. Then succinctly describe the edge computing, challenges faced in edge computing, and finally windup with the solutions and various edge computing applications. © Grenze Scientific Society, 2023.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Twitter Media Sentiment Analysis to Convert Non-Informative to Informative Using QER

引用

Intelligent Automation & Soft Computing 2023年第3期35卷 3545-3555页

作者： C.P.Thamil Selvi P.Muneeshwari K.Selvasheela D.Prasanna Department of Computer Science and Engineering Sri Ranganathar Institute of Engineering and TechnologyCoimbatore641009TamilnaduIndia Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Chennai602105Tamil NaduIndia Department of Computer Science and Engineering Sreesakthi Engineering CollegeKaramadai641104Tamil NaduIndia Department of Computer Science and Engineering Mahendra Engineering CollegeNamakkal637503Tamil NaduIndia

The term sentiment analysis deals with sentiment classiﬁcation based on the review made by the user in a social *** sentiment classiﬁcation accuracy is evaluated using various selection methods,especially those that deal with algorithm *** this work,every sentiment received through user expressions is ranked in order to categorise sentiments as informative and *** order to do so,the work focus on Query Expansion Ranking(QER)algorithm that takes user text as input and process for sentiment analysis andﬁnally produces the results as informative or *** challenge is to convert non-informative into informative using the concepts of classiﬁers like Bayes multinomial,entropy modelling along with the traditional sentimental analysis algorithm like Support Vector machine(SVM)and decision *** work also addresses simulated annealing along with QER to classify data based on sentiment *** the input volume is very fast,the work also addresses the concept of big data for information retrieval and *** result com-parison shows that the QER algorithm proved to be versatile when compared with the result of *** work uses Twitter user comments for evaluating senti-ment analysis.

关键词： Sentiments QER SVM bayes multinomial big data analysis simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Customer Segmentation Using Clustering Analysis

Customer Segmentation Using Clustering Analysis

引用

2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Jiet, Moses Makuei Kamble, Aahash Puri, Chetan Yesankar, Prajyot Verma, Prateek Rewatkar, Rajendra Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Biomedical Engineering Maharashtra Wardha442001 India

ISBN: (纸本)9798350382693

This research focuses on the crucial role of the clustering technique in data mining, specifically in market forecasting and planning. The study presents a comprehensive report on utilizing the k-means clustering technique and data visualization tools to develop a real- time system for a supermarket, predicting sales across various annual cycles. An open-source dataset of a mall with n = 200 customers divided into k = 3 groups, demonstrated high accuracy in predicting day-to-day sales statistics when compared with actual results. The research highlights the effectiveness of the clustering technique in real-time sales prediction for supermarkets. © 2024 IEEE.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

CRYPTOPASS - A Unified Password Manager

CRYPTOPASS - A Unified Password Manager

引用

2024 IEEE International Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Samuel, Prithi Vijay, K. Dheephiga, A.M. Maarcus Reniero, L. SRM Institute of Science and Technology Kattankulathur Campus Department of Computational Intelligence India Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Worldline Global Services Chennai India UST Chennai India

ISBN: (纸本)9798331522988

In the present scenario, many people are unaware of the security risks when they store their passwords or keys directly as a text file without encryption. This leaves your password exposed to hackers who can access them easily. This software aims to create only one strong password to ease the pressure of remembering passwords is very efficient for us as users. A dedicated password manager will store your passwords in an encrypted form, help you generate secure random passwords, offer a more powerful interface, and allow you to easily access your passwords across all the different computers, smartphones, and tablets you use. Keeping the above scenario in mind, this application is designed to enhance the security of user's data. This application is based on password vaults or password managers which are programs that keep your passwords in a secure location. When you use this software, the passwords are encrypted, and you use a single master password to access them. The basic idea is to create only one password to help to remember it as well as for efficient access. This increases the security of our accounts as well as the regulation of our passwords in a secure manner. The key components of reusability and flexibility are implemented in this project which makes the project even more user friendly and makes the user more comfortable towards using Cryptopass. © 2024 IEEE.

关键词： Cross-Platform Compatibility Cryptopass Master Password Password Encryption Password Vault Secure Access User-Friendly Interface

来源：评论

学校读者我要写书评

暂无评论

Incorporation of Deep learning (DL) Techniques to make Intelligent and Adaptable Wireless Communication Systems

Incorporation of Deep Learning (DL) Techniques to make Intel...

引用

2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023

作者： Tiwari, Anamika Kumar, Sandeep Rengarajan, A. Noida Institute of Engineering and Technology Department of Artificial Intelligence & Machine Learning Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350344387

The emergence of Deep learning (DL) was a response to the widespread availability of mobile data and the growing complexity of wireless networks. It is a subfield of machine learning that has been proposed in academic literature. This technology is regarded as a breakthrough in the management of mobile data traffic. Wireless systems generate a significant amount of varied data, which presents computational issues. In order to tackle this problem, a variety of optimization methodologies are being investigated. DL increases wireless communication by enhancing its intelligence and adaptability. This paper offers an overview of the DL platform and several methodologies employed to enable deep learning in wireless communications. Wireless networking involves various disciplines, including networking, routing, and scheduling, all of which incorporate DL. This text encompasses a comprehensive range of topics. The topic encompassed several optimization methodologies and the latest breakthroughs in this domain. © 2023 IEEE.

关键词： Deep learning Fog computing Mobile network Reinforcement learning Wireless network

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Review on Probable Measures for Addressing Security Limitations in Internet of Drones

A Comprehensive Review on Probable Measures for Addressing S...

引用

2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023

作者： Gupta, Gaurav Menaka, C. Padmanabhan, P. Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Artificial Intelligence & Machine Learning Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350344387

The Internet of Drones (IoD) has garnered significant interest in recent years due to its portable and automated nature and is being utilized across various domains such as the military, search and rescue operations, and entertainment. However, due to the inherently unsecured radio transmission paths in the Internet of Drones (IoD), there are numerous security concerns associated with the data collected, generated, or processed by drones. This paper aims to address the prominent challenges of security and privacy in the IoD. It undertakes a thorough examination of security concerns and corresponding solutions for IoD security. The discussion encompasses the security requirements associated with IoD and highlights the most recent advancements in research pertaining to IoD security. Authentication methods and Blockchain-based schemes are highlighted in this overview of numerous significant security technologies. Through an extensive analysis, we hereby present an examination of the challenges encountered by existing methodologies and propose potential avenues for future research in the field of IoT security. This review highlights the necessity of implementing suitable security measures to tackle IoT security concerns. Furthermore, it emphasizes the importance of developing security solutions that carefully consider the trade-off among the level of security provided and the cost efficiency of implementation. © 2023 IEEE.

关键词： Authentication Blockchain Internet of Drones (IoD) Privacy Security

来源：评论

学校读者我要写书评

暂无评论

Securing Digital Governance: A Deep learning and Blockchain Framework for Malware Detection in IoT Networks 2

Securing Digital Governance: A Deep Learning and Blockchain ...

引用

2nd IEEE International Conference on Integrated intelligence and Communication Systems, ICIICS 2024

作者： Pawar, Priyanka Pramod Kumar, Deepak Meesala, Mohan Kumar Pareek, Piyush Kumar Addula, Santosh Reddy Shwetha, K.S. Department of Information Technology University of the Cumberlands WilliamsburgKY United States Department of Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru India Department of Computer Science and Engineering Dayananda Sagar College of Engineering Bangalore India

ISBN: (纸本)9798331504960

This research uses deep learning and blockchain frameworks to provide a safe platform that promotes digital governance data exchange and interoperability. Use the bonobo optimization algorithm to start a blockchain-based smart city data authentication approach. This paper presents a Blockchain-based malware detection method and framework that uses AI to account for multiple distributed conditions. An upgraded greedy search algorithm and the XGBoost decision tree construct a two-layer extreme gradient boosting (XGBoost) classification model that detects attacks. Three pre-existing XGBoost significance indices were split and merged based on the model's leaf nodes' tree traversal structural features. The augmented greedy search technique retrieved and imported spectral band variables into the XGBoost model's second layer. Bat method was used to optimize XGBoost modeling parameters. The deployed model increased power consumption per device by 13.5%, while Raspberry Pi devices used 0.2 GB and NVIDIA Jetson devices used 0.42 GB. ML models had 93% f1-scores and 95% detection accuracy on both datasets. Our technology detects malware and attacks in Smart Environments efficiently and accurately, as shown by the models. © 2024 IEEE.

关键词： Decision trees

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：