{"title":"The Fascinating World of Cloud Robotics","authors":"Kasture Ab","doi":"10.23880/art-16000117","DOIUrl":"https://doi.org/10.23880/art-16000117","url":null,"abstract":"","PeriodicalId":518851,"journal":{"name":"Advances in Robotic Technology","volume":"16 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent times, Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly prevalent, fundamentally altering various industries and modernizing conventional methods. Their influence extends across a wide spectrum, ranging from financial technology to healthcare, robotics to quantum computing. This article offers an extensive examination of the intricate domain of AI and ML, highlighting their advancements and consequences across different sectors. Drawing upon scholarly research, patent disclosures, and academic literature, it investigates the pervasive impact of AI and ML on global industries and societies. Covering fundamental concepts and state-of-the-art applications, the article explores the interdisciplinary essence of AI and ML, emphasizing their transformative capacity and the ethical dilemmas accompanying their implementation. Through this analysis, the article seeks to illuminate the significant ramifications of AI and ML technologies, emphasizing the necessity for responsible management to maximize their benefits while addressing potential challenges.
近来，人工智能（AI）和机器学习（ML）日益普及，从根本上改变了各行各业，并使传统方法现代化。它们的影响范围广泛，从金融技术到医疗保健，从机器人技术到量子计算，不一而足。本文对人工智能和人工智能这一错综复杂的领域进行了广泛的研究，重点介绍了它们在不同领域的进步和影响。文章利用学术研究、专利披露和学术文献，探讨了人工智能和 ML 对全球各行业和社会的普遍影响。文章涵盖了基本概念和最新应用，探讨了人工智能和 ML 的跨学科本质，强调了它们的变革能力及其实施过程中的伦理困境。通过分析，文章试图阐明人工智能和 ML 技术的重大影响，强调有必要进行负责任的管理，以最大限度地发挥其效益，同时应对潜在的挑战。
{"title":"Unveiling the Technological Tapestry: Exploring the Transformative Influence of AI and ML across Diverse Domains","authors":"Jain R","doi":"10.23880/art-16000116","DOIUrl":"https://doi.org/10.23880/art-16000116","url":null,"abstract":"In recent times, Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly prevalent, fundamentally altering various industries and modernizing conventional methods. Their influence extends across a wide spectrum, ranging from financial technology to healthcare, robotics to quantum computing. This article offers an extensive examination of the intricate domain of AI and ML, highlighting their advancements and consequences across different sectors. Drawing upon scholarly research, patent disclosures, and academic literature, it investigates the pervasive impact of AI and ML on global industries and societies. Covering fundamental concepts and state-of-the-art applications, the article explores the interdisciplinary essence of AI and ML, emphasizing their transformative capacity and the ethical dilemmas accompanying their implementation. Through this analysis, the article seeks to illuminate the significant ramifications of AI and ML technologies, emphasizing the necessity for responsible management to maximize their benefits while addressing potential challenges.","PeriodicalId":518851,"journal":{"name":"Advances in Robotic Technology","volume":"5 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research article investigates the effectiveness of natural language processing (NLP) and supervised learning in classifying fake news articles. With the increasing prevalence of fake news in online media, it has become critical to identify and categorize such articles accurately. In this study, we apply NLP techniques to extract features from textual data, and use a supervised learning algorithm to train a classification model. We use a dataset of fake news articles to evaluate the performance of our model in terms of accuracy, precision, recall, and F1 score. Our results demonstrate that our approach achieved high accuracy and robustness in the classification of fake news articles. Furthermore, we perform a feature importance analysis to identify the most significant features that contribute to the classification of fake news. The findings of this study have practical implications for identifying and combating fake news in online media, and also provide insights into the effectiveness of NLP and supervised learning for text classification tasks.
这篇研究文章探讨了自然语言处理（NLP）和监督学习在假新闻文章分类中的有效性。随着假新闻在网络媒体中日益盛行，准确识别和分类此类文章变得至关重要。在本研究中，我们应用 NLP 技术从文本数据中提取特征，并使用监督学习算法训练分类模型。我们使用假新闻文章数据集来评估模型在准确率、精确度、召回率和 F1 分数方面的性能。结果表明，我们的方法在假新闻文章分类方面实现了较高的准确性和鲁棒性。此外，我们还进行了特征重要性分析，以确定有助于假新闻分类的最重要特征。本研究的发现对识别和打击网络媒体中的假新闻具有实际意义，同时也为 NLP 和监督学习在文本分类任务中的有效性提供了启示。
{"title":"Exploring the Efficacy of Natural Language Processing and Supervised Learning in the Classification of Fake News Articles","authors":"Jain R","doi":"10.23880/art-16000108","DOIUrl":"https://doi.org/10.23880/art-16000108","url":null,"abstract":"This research article investigates the effectiveness of natural language processing (NLP) and supervised learning in classifying fake news articles. With the increasing prevalence of fake news in online media, it has become critical to identify and categorize such articles accurately. In this study, we apply NLP techniques to extract features from textual data, and use a supervised learning algorithm to train a classification model. We use a dataset of fake news articles to evaluate the performance of our model in terms of accuracy, precision, recall, and F1 score. Our results demonstrate that our approach achieved high accuracy and robustness in the classification of fake news articles. Furthermore, we perform a feature importance analysis to identify the most significant features that contribute to the classification of fake news. The findings of this study have practical implications for identifying and combating fake news in online media, and also provide insights into the effectiveness of NLP and supervised learning for text classification tasks.","PeriodicalId":518851,"journal":{"name":"Advances in Robotic Technology","volume":"13 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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