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Topic Review
Textile-Based Sensors for Biosignal Detection
Biosignals often have to be detected in sports or for medical reasons. Typical biosignals are pulse and ECG (electrocardiogram), breathing, blood pressure, skin temperature, oxygen saturation, bioimpedance, etc. Typically, scientists attempt to measure these biosignals noninvasively, i.e., with electrodes or other sensors, detecting electric signals, measuring optical or chemical information.
  • 671
  • 13 Sep 2021
Topic Review
Text Mining and Software Metrics in Vulnerability Prediction
Vulnerability prediction is a mechanism that facilitates the identification (and, in turn, the mitigation) of vulnerabilities early enough during the software development cycle. The scientific community has recently focused a lot of attention on developing Deep Learning models using text mining techniques and software metrics for predicting the existence of vulnerabilities in software components. However, limited attention has been given on the comparison and the combination of text mining- based and software metrics- based vulnerability prediction models.
  • 663
  • 02 Jun 2022
Topic Review
Text Line Segmentation from Malayalam Documents
After the pandemic situation created by the novel coronavirus, it has become a necessity to encode the local language, conventionally written in pen and paper, in an electronic format. Optical character recognition (OCR) systems convert handwritten documents to a computer-editable digital form. Optical character recognition (OCR) converts pdf files, scanned documents, images containing text and printed and handwritten documents into editable electronic documents. OCR can be implemented for printed character recognition and handwritten character recognition. The latter is further categorized into online and offline recognition systems. Optical Character Recognition system for Malayalam handwritten documents has become an open research area. A major hindrance for this research is the unavailability of a benchmark database. Therefore, a new database of 402 Malayalam handwritten document images and ground truth images of 7535 text lines is developed for the implementation of the proposed technique. This paper proposes a technique for extracting text lines from handwritten documents in Malayalam language, specifically based on the handwriting of the writer. Text lines are extracted based on horizontal and vertical projection values, size of the handwritten characters, height of the text lines and the curved nature of Malayalam alphabets.
  • 291
  • 22 Sep 2023
Topic Review
Text Generation Models and Imbalanced Sentiment Analysis
The significance of sentiment analysis has extended across a wide range of fields, finding extensive use in various applications. As digital communication continues to expand, the ability of sentiment analysis to interpret complex human emotions and opinions becomes increasingly important, proving invaluable in fields ranging from social sciences to customer service and beyond. In this era of increasing digitization, leveraging the power of data through sentiment analysis offers unique insights, making significant contributions to sectors such as those previously summarized in various studies, namely, healthcare, social policy, e-commerce, and digital humanities.
  • 225
  • 18 Sep 2023
Topic Review
Text Emotions on Non-English Datasets
Machine learning approaches, in particular graph learning methods, have achieved great results in the field of natural language processing, in particular text classification tasks. However, many of such models have shown limited generalization on datasets in different languages. 
  • 261
  • 23 Oct 2023
Topic Review
Text Classification Technique
One of the effective solutions in Arabic text classification is to find the suitable feature selection method with an optimal number of features alongside the classifier. Although several text classification methods have been proposed for the Arabic language using different techniques, such as feature selection methods, an ensemble of classifiers, and discriminative features, choosing the optimal method becomes an NP-hard problem considering the huge search space. 
  • 278
  • 02 Mar 2023
Topic Review
Text Classification Algorithms: A Survey
In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches have achieved surpassing results in natural language processing. The success of these learning algorithms relies on their capacity to understand complex models and non-linear relationships within data. However, finding suitable structures, architectures, and techniques for text classification is a challenge for researchers. In this paper, a brief overview of text classification algorithms is discussed. This overview covers different text feature extractions, dimensionality reduction methods, existing algorithms and techniques, and evaluation methods. Finally, the limitations of each technique and its application in real-world problems are discussed.
  • 1.1K
  • 08 Feb 2021
Topic Review
Tether (Cryptocurrency)
Tether (often referred to by one of its currency codes, USD₮), is an asset-backed cryptocurrency stablecoin. It was launched by the company Tether Limited Inc. in 2014. Tether Limited is owned by the Hong Kong-based company iFinex Inc., which also owns the Bitfinex cryptocurrency exchange. As of July 2022, Tether Limited has minted the USDT stablecoin on ten protocols and blockchains. Tether is described as a stablecoin because it was originally designed to be valued at USD $1.00, with Tether Limited maintaining USD $1.00 of asset reserves for each USDT issued.
  • 2.2K
  • 16 Nov 2022
Topic Review
Test-Time Augmentation for Network Anomaly Detection
Machine learning-based Network Intrusion Detection Systems (NIDS) are designed to protect networks by identifying anomalous behaviors or improper uses. In recent years, advanced attacks, such as those mimicking legitimate traffic, have been developed to avoid alerting such systems. Test-Time Augmentation for Network Anomaly Detection (TTANAD), which utilizes test-time augmentation to enhance anomaly detection from the data side.
  • 167
  • 28 Jul 2023
Topic Review
Test Generation
Test generation is the process of creating a set of test data or test cases for testing the adequacy of new or revised software applications. Test Generation is seen to be a complex problem and though a lot of solutions have come forth most of them are limited to toy programs. Test Generation is one aspect of software testing. Since testing is labor-intensive, accounting for nearly one third of the cost of the system development, the problem of generating quality test data quickly, efficiently and accurately is seen to be important.
  • 928
  • 30 Nov 2022
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