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Information, Volume 14, Issue 3

March 2023 - 61 articles

Cover Story: The emergence of COVID-19 generated a need for accurate timely information related to its spread. We propose two methods for using Twitter to help model the spread of COVID-19: machine learning algorithms trained in five languages are used to identify symptomatic individuals; using the geo-location attached to each tweet, we also map where people have symptoms. We calibrated an epidemiological model and then evaluated the usefulness of the data when making predictions of deaths in 50 US States, 16 Latin American countries, 2 European countries and 7 regions in the UK. Using such tweets from symptomatic individuals results in improvements in accuracy when predicting COVID-19 deaths. We also show we can extract useful data describing movements between UK regions. View this paper
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Articles (61)

  • Article
  • Open Access
2 Citations
2,938 Views
24 Pages

17 March 2023

Semi-supervised learning is a technique that utilizes a limited set of labeled data and a large amount of unlabeled data to overcome the challenges of obtaining a perfect dataset in deep learning, especially in medical image segmentation. The accurac...

  • Article
  • Open Access
3 Citations
2,744 Views
18 Pages

17 March 2023

Helium speech, the language spoken by divers in the deep sea who breathe a high-pressure helium–oxygen mixture, is almost unintelligible. To accurately unscramble helium speech, a neural network based on deep learning is proposed. First, an iso...

  • Article
  • Open Access
2 Citations
2,869 Views
17 Pages

Ontology-Driven Knowledge Sharing in Alzheimer’s Disease Research

  • Sophia Lazarova,
  • Dessislava Petrova-Antonova and
  • Todor Kunchev

16 March 2023

Alzheimer’s disease is a debilitating neurodegenerative condition which is known to be the most common cause of dementia. Despite its rapidly growing prevalence, medicine still lacks a comprehensive definition of the disease. As a result, Alzhe...

  • Review
  • Open Access
56 Citations
16,162 Views
25 Pages

16 March 2023

Transfer learning is a technique utilized in deep learning applications to transmit learned inference to a different target domain. The approach is mainly to solve the problem of a few training datasets resulting in model overfitting, which affects m...

  • Article
  • Open Access
7 Citations
4,628 Views
19 Pages

A Quick Prototype for Assessing OpenIE Knowledge Graph-Based Question-Answering Systems

  • Giuseppina Di Paolo,
  • Diego Rincon-Yanez and
  • Sabrina Senatore

16 March 2023

Due to the rapid growth of knowledge graphs (KG) as representational learning methods in recent years, question-answering approaches have received increasing attention from academia and industry. Question-answering systems use knowledge graphs to org...

  • Article
  • Open Access
14 Citations
4,008 Views
15 Pages

16 March 2023

Aspect-based sentiment analysis is a fine-grained sentiment analysis that focuses on the sentiment polarity of different aspects of text, and most current research methods use a combination of dependent syntactic analysis and graphical neural network...

  • Article
  • Open Access
14 Citations
6,902 Views
21 Pages

15 March 2023

A tremendous amount of image and video data are being generated and shared in our daily lives. Image and video data are typically stored and transmitted in compressed form in order to reduce storage space and transmission time. The processing and ana...

  • Article
  • Open Access
7 Citations
2,540 Views
11 Pages

15 March 2023

The automatic recognition of CT (Computed Tomography) images of liver cancer is important for the diagnosis and treatment of early liver cancer. However, there are problems such as single model structure and loss of pooling layer information when usi...

  • Article
  • Open Access
4 Citations
3,366 Views
11 Pages

15 March 2023

As road mileage continues to expand, the number of disasters caused by expanding pavement cracks is increasing. Two main methods, image processing and deep learning, are used to detect these cracks to improve the efficiency and quality of pavement cr...

  • Article
  • Open Access
3 Citations
6,981 Views
17 Pages

Smart Machine Health Prediction Based on Machine Learning in Industry Environment

  • Sagar Yeruva,
  • Jeshmitha Gunuganti,
  • Sravani Kalva,
  • Surender Reddy Salkuti and
  • Seong-Cheol Kim

14 March 2023

In an industrial setting, consistent production and machine maintenance might help any company become successful. Machine health checking is a method of observing the status of a machine to predict mechanical mileage and predict the machine’s d...

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Information - ISSN 2078-2489