Inverse design, where we seek to design input variables in order to optimize an underlying objective function, is an important problem that arises across fields such as mechanical engineering to aerospace engineering....
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Transportation systems that are intelligent are developing for the benefit of travelers. The transportation business has suffered greatly as a result of advanced technology like the Internet of Things (IoT). Ensuring ...
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In the evolving landscape of medical software security, the threat of command injection looms large, with potential ramifications including compromised patient data and disrupted healthcare services. Addressing these ...
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A Nobel approach to the password management system is introduced in this paper, which is through a decentralized system named blockchain. Our goal is to secure people's passwords by providing them with a secure an...
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Conventional lexicon-based approaches to sentiment analysis typically lack the necessary methods to properly identify the negation window, making it impossible to model negation. An enormous increase in sentiment-rich...
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ISBN:
(纸本)9798350359688
Conventional lexicon-based approaches to sentiment analysis typically lack the necessary methods to properly identify the negation window, making it impossible to model negation. An enormous increase in sentiment-rich electronic and social media has been observed daily. Negation modifiers cause problems for Sentiment Classification techniques and have the power to entirely change the discourse's meaning. Therefore, it becomes essential to manage them well. Opinion mining or sentiment analysis is the study of people's attitudes, feelings, and views as they are expressed in written language. It is one of the busiest text mining and natural language processing research projects. Even though sentiment analysis research has gained popularity in the field of natural language processing, for this problem, the state-of-the-art machine learning approach is based on Bag of Words. But the BOW model pays little attention to polarity shift, which could have a distinct overall effect. One of the main issues with doing sentimental analysis on any given text or sentence is handling polarity shift, which is what this study attempts to address. Sentiment analysis use Natural Language Processing principles to identify negation in the text. Our goal is to identify the negation effect on customer reviews that, although appearing good, are actually negative. The suggested modified negation methodology helps to increase classification accuracy by providing a method for computing negation identification. In terms of review classification by accuracy, precision, and recall, this approach yielded a noteworthy outcome. When test and training data are from distinct domains, machine learning faces the challenge of domain generalization. Despite the large body of research on cross-domain text classification, the majority of current methods concentrate on one-to-one or many-to-one domain adaptation. Our domain generalization method regularly outperforms state-of-the-art domain adaption methods, a
The MQTT (Message Queuing Telemetry Transport) protocol has become the standard for IoT (Internet of Things) communication due to its lightweight nature and efficiency. However, its centralized architecture, with a si...
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As the spine innovation of decentralized cryptocurrencies, blockchain has additionally proclaimed numerous applications in different fields, for example, resource allocation in cloud computing, Internet of Things (IoT...
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Website Fingerprinting (WF) is a statistical traffic analysis attack, that allows a local, passive eavesdropper to determine a client’s web activity by leveraging features from her packet sequence. These attacks brea...
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The analysis of fiscal position represents significant in the encouragement of economic stability and development specifically to the country like Kenya. This work employs the clustering analysis technique in order to...
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Image captioning, which exists at the point of intersection of computer vision and natural language processing, is essential for enhancing image comprehension, allowing applications like content discovery, visual aid ...
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