B5G/6G networks are facing challenges in the deployment of additional base stations. However, Taiwan's four major operators have launched VoWi-Fi calling services to maintain signal quality and coverage for custom...
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The volume of user-generated content that the social media space, particularly that of Reddit, produces is unprecedented, which now can be considered an excellent source of analysis for the study of public opinion and...
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ISBN:
(纸本)9798331523923
The volume of user-generated content that the social media space, particularly that of Reddit, produces is unprecedented, which now can be considered an excellent source of analysis for the study of public opinion and communication trends. However, such huge unstructured text pieces also pose several problems for analytics that are exacerbated in the presence of noise in the texts, non-standard variations of language usage, sarcasm, and so forth, as well as the requirements for scalable modes of computation. Although new advances in Natural Language Processing(NLP) like BERT and RoBERTa do much better than their previous transformer-based models, at a great computational cost, there is also an enormous labeled dataset to fine-tune. Light in weight but falling flat where the situation might be ambiguous based on the context or subtlety in the expression, there are lexicon-based traditional methods like VADER and TextBlob. A Python-based system that uses advanced NLP techniques for sentiment and tone analysis of Reddit posts. The study categorizes the sentiments as positive, negative, and neutral. The tones were also kept in mind, differentiating formal posts from informal ones. The methodology undertaken was a step-by-step approach, fetching data from the Reddit API, preprocessed removal of noise, and text that is absolutely irrelevant. VADER and TextBlob have been employed to perform sentiment analysis. Developing a tone detection method depends on linguistic features such as vocabulary complexity, sentence structure, and punctuation usage. It was written with respect to computational efficiency and scalability, using Python libraries such as NumPy, NLTK, MatplotLib and spaCy. This work contributes to social media analytics through an inclusive and scalable framework for potential application in analyzing complex unstructured textual data. This maps the generalization to brand reputation management, public policy planning, and content management activities, all of w
The earlier research clearly indicated that the bimodal authentication system has more efficiency than unimodal and multimodal. This is due to the reason for the best intact biometric traits of fingerprint and retina....
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In light of growing health worries, this study introduces an innovative system for relating stress by combining the power of the Internet of Effects (IoT) and machine literacy (ML). The' Stress. lysis' collect...
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The main goal of this research is to apply cutting-edge machine learning methods to predict maize leaf disease more accurately. Crucial staple crop maize is susceptible to a number of leaf diseases that can have a maj...
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Cloud Computing (CC) generally exhibits varying workload patterns. This autoscaling feature of CC has been extensively managed through predictive cloud resource management approaches. For this reason, a solitary forec...
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This paper introduces an IoT-based smart medicine box which is used to enhance medicine management and patient care. It incorporates a number of functions including a box with servo motor accompanied by LED and buzzer...
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Inpatient falls from beds in hospitals are a common *** falls may result in severe *** problem can be addressed by continuous monitoring of patients using *** advancements in deep learning-based video analytics have m...
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Inpatient falls from beds in hospitals are a common *** falls may result in severe *** problem can be addressed by continuous monitoring of patients using *** advancements in deep learning-based video analytics have made this task of fall detection more effective and *** with fall detection,monitoring of different activities of the patients is also of significant concern to assess the improvement in their *** computation-intensive models are required to monitor every action of the patient *** requirement limits the applicability of such ***,to keep the model lightweight,the already designed fall detection networks can be extended to monitor the general activities of the patients along with the fall *** by the same notion,we propose a novel,lightweight,and efficient patient activity monitoring system that broadly classifies the patients’activities into fall,activity,and rest classes based on their *** whole network comprises three sub-networks,namely a Convolutional Neural Networks(CNN)based video compression network,a Lightweight Pose Network(LPN)and a Residual Network(ResNet)Mixer block-based activity recognition *** compression network compresses the video streams using deep learning networks for efficient storage and retrieval;after that,LPN estimates human ***,the activity recognition network classifies the patients’activities based on their *** proposed system shows an overall accuracy of approx.99.7% over a standard dataset with 99.63% fall detection accuracy and efficiently monitors different events,which may help monitor the falls and improve the inpatients’health.
Work-integrated learning (WIL) combines academic learning with practical work experiences, helping students transition smoothly from theory to real-world application. This paper explores the effectiveness of WIL progr...
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Entanglement plays a vital role in quantum information *** to its unique material properties,silicon carbide recently emerged as a promising candidate for the scalable implementation of advanced quantum information pr...
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Entanglement plays a vital role in quantum information *** to its unique material properties,silicon carbide recently emerged as a promising candidate for the scalable implementation of advanced quantum information processing *** date,however,only entanglement of nuclear spins has been reported in silicon carbide,while an entangled photon source,whether it is based on bulk or chip-scale technologies,has remained ***,we report the demonstration of an entangled photon source in an integrated silicon carbide platform for the first ***,strongly correlated photon pairs are efficiently generated at the telecom C-band wavelength through implementing spontaneous four-wave mixing in a compact microring resonator in the 4H-silicon-carbide-on-insulator *** maximum coincidence-to-accidental ratio exceeds 600 at a pump power of 0.17 mW,corresponding to a pair generation rate of(9±1)×10^(3) pairs/***-time entanglement is created and verified for such signal-idler photon pairs,with the two-photon interference fringes exhibiting a visibility larger than 99%.The heralded single-photon properties are also measured,with the heralded g^((2))(0)on the order of 10^(−3),demonstrating the SiC platform as a prospective fully integrated,complementary metal-oxide-semiconductor compatible single-photon source for quantum applications.
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